Monitoring drought conditions and their uncertainties in Africa using TRMM data

Autores
Naumann, Gustavo; Barbosa, P.; Carrao, H.; Singleton, A.; Vogt, J.
Año de publicación
2012
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The main objective of this study is to evaluate the uncertainties due to sample size associated with the estimation of the standardized precipitation index (SPI) and their impact on the level of confidence in drought monitoring in Africa using high-spatial-resolution data from short time series. To do this, two different rainfall datasets, each available on a monthly basis, were analyzed over four river basins in Africa-Oum er-Rbia, Limpopo, Niger, and eastern Nile-as well as at the continental level. The two precipitation datasets used were the Tropical Rainfall Measuring Mission (TRMM) satellite monthly rainfall product 3B43 and the Global Precipitation Climatology Centre full-reanalysis gridded precipitation dataset. A nonparametric resampling bootstrap approach was used to compute the confidence bands associated with the SPI estimation, which are essential for making a qualified assessment of drought events. The comparative analysis of different datasets suggests that for reliable drought monitoring over Africa it is feasible to use short time series of remote sensing precipitation data, such as those from TRMM, that have a higher spatial resolution than other gridded precipitation data. The proposed approach for drought monitoring has the potential to be used in support of decision making at both continental and subcontinental scales over Africa or over other regions that have a sparse distribution of rainfall measurement instruments.
Fil: Naumann, Gustavo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina. Joint Research Centre. Institute for Environment and Sustainability; Italia
Fil: Barbosa, P.. Joint Research Centre. Institute for Environment and Sustainability; Italia
Fil: Carrao, H.. Joint Research Centre. Institute for Environment and Sustainability; Italia
Fil: Singleton, A.. Joint Research Centre. Institute for Environment and Sustainability; Italia
Fil: Vogt, J.. Joint Research Centre. Institute for Environment and Sustainability; Italia
Materia
AFRICA
BIAS
COMMUNICATIONS/DECISION MAKING
DROUGHT
RAINFALL
SATELLITE OBSERVATIONS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/216441
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/216441
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Monitoring drought conditions and their uncertainties in Africa using TRMM dataNaumann, GustavoBarbosa, P.Carrao, H.Singleton, A.Vogt, J.AFRICABIASCOMMUNICATIONS/DECISION MAKINGDROUGHTRAINFALLSATELLITE OBSERVATIONShttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1The main objective of this study is to evaluate the uncertainties due to sample size associated with the estimation of the standardized precipitation index (SPI) and their impact on the level of confidence in drought monitoring in Africa using high-spatial-resolution data from short time series. To do this, two different rainfall datasets, each available on a monthly basis, were analyzed over four river basins in Africa-Oum er-Rbia, Limpopo, Niger, and eastern Nile-as well as at the continental level. The two precipitation datasets used were the Tropical Rainfall Measuring Mission (TRMM) satellite monthly rainfall product 3B43 and the Global Precipitation Climatology Centre full-reanalysis gridded precipitation dataset. A nonparametric resampling bootstrap approach was used to compute the confidence bands associated with the SPI estimation, which are essential for making a qualified assessment of drought events. The comparative analysis of different datasets suggests that for reliable drought monitoring over Africa it is feasible to use short time series of remote sensing precipitation data, such as those from TRMM, that have a higher spatial resolution than other gridded precipitation data. The proposed approach for drought monitoring has the potential to be used in support of decision making at both continental and subcontinental scales over Africa or over other regions that have a sparse distribution of rainfall measurement instruments.Fil: Naumann, Gustavo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina. Joint Research Centre. Institute for Environment and Sustainability; ItaliaFil: Barbosa, P.. Joint Research Centre. Institute for Environment and Sustainability; ItaliaFil: Carrao, H.. Joint Research Centre. Institute for Environment and Sustainability; ItaliaFil: Singleton, A.. Joint Research Centre. Institute for Environment and Sustainability; ItaliaFil: Vogt, J.. Joint Research Centre. Institute for Environment and Sustainability; ItaliaAmer Meteorological Soc2012-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/216441Naumann, Gustavo; Barbosa, P.; Carrao, H.; Singleton, A.; Vogt, J.; Monitoring drought conditions and their uncertainties in Africa using TRMM data; Amer Meteorological Soc; Journal Of Applied Meteorology And Climatology; 51; 10; 10-2012; 1867-18741558-8424CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://journals.ametsoc.org/view/journals/apme/51/10/jamc-d-12-0113.1.xmlinfo:eu-repo/semantics/altIdentifier/doi/10.1175/JAMC-D-12-0113.1info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:40:39Zoai:ri.conicet.gov.ar:11336/216441instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 14:40:39.524CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Monitoring drought conditions and their uncertainties in Africa using TRMM data
title Monitoring drought conditions and their uncertainties in Africa using TRMM data
spellingShingle Monitoring drought conditions and their uncertainties in Africa using TRMM data
Naumann, Gustavo
AFRICA
BIAS
COMMUNICATIONS/DECISION MAKING
DROUGHT
RAINFALL
SATELLITE OBSERVATIONS
title_short Monitoring drought conditions and their uncertainties in Africa using TRMM data
title_full Monitoring drought conditions and their uncertainties in Africa using TRMM data
title_fullStr Monitoring drought conditions and their uncertainties in Africa using TRMM data
title_full_unstemmed Monitoring drought conditions and their uncertainties in Africa using TRMM data
title_sort Monitoring drought conditions and their uncertainties in Africa using TRMM data
dc.creator.none.fl_str_mv Naumann, Gustavo
Barbosa, P.
Carrao, H.
Singleton, A.
Vogt, J.
author Naumann, Gustavo
author_facet Naumann, Gustavo
Barbosa, P.
Carrao, H.
Singleton, A.
Vogt, J.
author_role author
author2 Barbosa, P.
Carrao, H.
Singleton, A.
Vogt, J.
author2_role author
author
author
author
dc.subject.none.fl_str_mv AFRICA
BIAS
COMMUNICATIONS/DECISION MAKING
DROUGHT
RAINFALL
SATELLITE OBSERVATIONS
topic AFRICA
BIAS
COMMUNICATIONS/DECISION MAKING
DROUGHT
RAINFALL
SATELLITE OBSERVATIONS
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The main objective of this study is to evaluate the uncertainties due to sample size associated with the estimation of the standardized precipitation index (SPI) and their impact on the level of confidence in drought monitoring in Africa using high-spatial-resolution data from short time series. To do this, two different rainfall datasets, each available on a monthly basis, were analyzed over four river basins in Africa-Oum er-Rbia, Limpopo, Niger, and eastern Nile-as well as at the continental level. The two precipitation datasets used were the Tropical Rainfall Measuring Mission (TRMM) satellite monthly rainfall product 3B43 and the Global Precipitation Climatology Centre full-reanalysis gridded precipitation dataset. A nonparametric resampling bootstrap approach was used to compute the confidence bands associated with the SPI estimation, which are essential for making a qualified assessment of drought events. The comparative analysis of different datasets suggests that for reliable drought monitoring over Africa it is feasible to use short time series of remote sensing precipitation data, such as those from TRMM, that have a higher spatial resolution than other gridded precipitation data. The proposed approach for drought monitoring has the potential to be used in support of decision making at both continental and subcontinental scales over Africa or over other regions that have a sparse distribution of rainfall measurement instruments.
Fil: Naumann, Gustavo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina. Joint Research Centre. Institute for Environment and Sustainability; Italia
Fil: Barbosa, P.. Joint Research Centre. Institute for Environment and Sustainability; Italia
Fil: Carrao, H.. Joint Research Centre. Institute for Environment and Sustainability; Italia
Fil: Singleton, A.. Joint Research Centre. Institute for Environment and Sustainability; Italia
Fil: Vogt, J.. Joint Research Centre. Institute for Environment and Sustainability; Italia
description The main objective of this study is to evaluate the uncertainties due to sample size associated with the estimation of the standardized precipitation index (SPI) and their impact on the level of confidence in drought monitoring in Africa using high-spatial-resolution data from short time series. To do this, two different rainfall datasets, each available on a monthly basis, were analyzed over four river basins in Africa-Oum er-Rbia, Limpopo, Niger, and eastern Nile-as well as at the continental level. The two precipitation datasets used were the Tropical Rainfall Measuring Mission (TRMM) satellite monthly rainfall product 3B43 and the Global Precipitation Climatology Centre full-reanalysis gridded precipitation dataset. A nonparametric resampling bootstrap approach was used to compute the confidence bands associated with the SPI estimation, which are essential for making a qualified assessment of drought events. The comparative analysis of different datasets suggests that for reliable drought monitoring over Africa it is feasible to use short time series of remote sensing precipitation data, such as those from TRMM, that have a higher spatial resolution than other gridded precipitation data. The proposed approach for drought monitoring has the potential to be used in support of decision making at both continental and subcontinental scales over Africa or over other regions that have a sparse distribution of rainfall measurement instruments.
publishDate 2012
dc.date.none.fl_str_mv 2012-10
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/216441
Naumann, Gustavo; Barbosa, P.; Carrao, H.; Singleton, A.; Vogt, J.; Monitoring drought conditions and their uncertainties in Africa using TRMM data; Amer Meteorological Soc; Journal Of Applied Meteorology And Climatology; 51; 10; 10-2012; 1867-1874
1558-8424
CONICET Digital
CONICET
url http://hdl.handle.net/11336/216441
identifier_str_mv Naumann, Gustavo; Barbosa, P.; Carrao, H.; Singleton, A.; Vogt, J.; Monitoring drought conditions and their uncertainties in Africa using TRMM data; Amer Meteorological Soc; Journal Of Applied Meteorology And Climatology; 51; 10; 10-2012; 1867-1874
1558-8424
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://journals.ametsoc.org/view/journals/apme/51/10/jamc-d-12-0113.1.xml
info:eu-repo/semantics/altIdentifier/doi/10.1175/JAMC-D-12-0113.1
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Amer Meteorological Soc
publisher.none.fl_str_mv Amer Meteorological Soc
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1846082899240026112
score 13.22299

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